Map Information Correction Device Using Sensor Data
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Solution Overview
Problem
Existing map data correction systems rely on subjective user input and require manual verification, leading to inefficiencies and inaccuracies due to variability in user perception and operational behavior.
Innovation Solution
A map information correction device and system that utilizes exterior environment recognition sensors and vehicle position estimation to determine differences in map information, generating correction data based on lane change and dividing line information, which is then transmitted to a map server for updating.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual verification by map database personnel is used to correct map data, then subjective accuracy may be improved, but workload and time consumption increase significantly
Solution Approach 1:
The patent replaces the mechanical manual verification process with an automated system using exterior environment recognition sensors (cameras, LIDAR) to capture road images and divideing line information. The system automatically compares sensor data with map database information to detect discrepancies, eliminating the need for manual field investigation while maintaining correction accuracy.
Solution Approach 2:
The map correction system performs self-verification by automatically comparing real-time sensor data with stored map information. The system independently identifies discrepancies in divideing lines and road features, generates correction information, and transmits it to the map database without requiring external manual intervention, thereby reducing workload while maintaining accuracy.
2Reliability
If manual field investigation is conducted to verify map data corrections, then correction reliability improves, but productivity decreases
Solution Approach 1:
The system replaces manual field investigation with automated sensor-based verification. Exterior environment recognition sensors continuously capture road images and divideing line information, which are automatically compared with map database records. This mechanical substitution maintains correction reliability through objective sensor data while dramatically improving productivity by eliminating time-consuming manual verification.
Solution Approach 2:
The system enables continuous map data verification by continuously capturing exterior environment information as the vehicle travels. Unlike discrete manual investigations, the automated system performs ongoing comparison and detection of map discrepancies in real-time, maintaining reliable correction accuracy while significantly increasing the volume of map data that can be verified per unit time.
3Measurement precision
If comprehensive map verification is performed manually, then measurement precision improves, but device complexity and operational difficulty increase
Solution Approach 1:
The system uses multi-functional exterior environment recognition sensors that simultaneously capture road images, detect divideing line information, and identify road features. This universal sensing approach achieves comprehensive map verification with a single integrated system rather than multiple specialized devices, maintaining measurement precision while reducing operational complexity.
Data Source
AI summary
An object of the present invention is to determine a difference on a map by using an exterior environment recognition sensor of a traveling vehicle and host vehicle position estimation information on the basis of existing map information and to enable the difference to be transmitted to a map server. According to the present invention, there is provided an in-vehicle map information correction device that corrects map information, the map information correction device including: a map holding unit (102) that holds the map information; a position estimation unit (104) that estimates position information on a vehicle; at least one of a lane change information acquisition unit (106) that acquires lane change information indicating whether or not the vehicle has changed a lane and a dividing line information acquisition unit (105) that acquires information on a dividing line type of a road on which the vehicle is traveling; and a difference determination unit (103) that generates correction information for correcting the map information based on at least one of the position information, the lane change information, and the information on the dividing line type.